Deriving Knowledge from Figures for Digital Libraries

Xiaonan Lu, James Z. Wang, Prasenjit Mitra, and C. Lee Giles
The Pennsylvania State University

Figures in digital documents contain important information. Current digital libraries do not summarize and index information available within figures for document retrieval. We present our system on automatic categorization of figures and extraction of data from 2-D plots. A machinelearning based method is used to categorize figures into a set of predefined types based on image features. An automated algorithm is designed to extract data values from solid line curves in 2-D plots. The semantic type of figures and extracted data values from 2-D plots can be integrated with textual information within documents to provide more effective document retrieval services for digital library users. Experimental evaluation has demonstrated that our system can produce results suitable for real-world use.

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Citation: Xiaonan Lu, James Z. Wang, Prasenjit Mitra, and C. Lee Giles, ``Deriving Knowledge from Figures for Digital Libraries,'' Proceedings of the International World Wide Web Conference, pp. 1229-1230, Banff, Alberta, Canada, May 2007.

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Last Modified: March 12, 2007.
© 2007, James Z. Wang